1. Field of the Invention
The present invention relates to a matching search method and a matching search system, and more particularly, to a matching search method and a matching search system capable of dynamically determining a search position and a search range according to image data.
2. Description of the Prior Art
With continuously progressing image technologies, sizes and functionalities of display devices are increasingly diverse. In order to meet requirements of the different consumers, manufacturers of the display devices try to provide new products with better outputting performance and resolution. One of the most interesting products is a display device with three-dimensional display functionality. General three-dimensional display technologies include polarized, interlaced or anaglyph display methods. These display methods utilize special optical structures to project images with different views corresponding to depth information on human left and right eyes. Thus, the human left and right eyes may respectively capture the images with different views to be synthesized by the human brain, and the human may sense a three-dimensional image.
When two-dimensional images without the depth information are displayed by the display device having the three-dimensional display functionality, since the source images for displaying lack the depth information, the display device may not generate multi-views images corresponding to the depth information to be projected on the human left and right eyes. Under such a condition, the display device is required to analyze the two-dimensional images to obtain the depth information, so as to display the multi-views images. In the prior art, at least two images with different views are required to be obtained first by utilizing multiples image capture devices located in different locations, and the depth information may be analyzed from the at least two images with different views. A process for analyzing two images with different views to obtain the depth information is called stereo matching. In the stereo matching, a matching search is performed first between the two images with different views, and matching objects (or characteristics, pixels, etc.) are searched to obtain positional differences of the matching objects in the two images with different views. The positional differences are disparity information (or can be called a disparity map) of the two images, and the depth information of the matching objects may be calculated by the disparity information.
However, since landscapes of the two images with different views are not entirely the same, in the prior art, the matching search is performed within the entire data range of the two images to obtain an accurate matching search result. Under such a condition, more computing cost for the matching search is required, such as more computing time, more hardware cost, or more power consumption, etc. When the resolution of the image is higher, such as a high-definition image, the data range is wider and the computing cost of the matching search is respectively increased. Therefore, how to determine the search range of the matching search for saving the computing cost and not affecting accuracy of the matching search result has become a most important topic in the stereo matching technologies.